Generating a ranked list of best fitting place names

ABSTRACT

A method of updating a plurality of databases storing place names includes collecting first, second and third coordinates of addresses including a first, a second and a third place name, respectively, clustering the first, second and third coordinates in a first, a second and a third cluster, respectively, obtaining a base address including the first place name and having base coordinates, assessing the best fit of the base coordinates to the first, second, and third clusters, and based on the two best fit clusters, identifying the second or third place name as an alias place name for the first place name. The method further includes obtaining alias addresses including the alias place name, fuzzy matching the base address to an alias address, and updating first and second databases by linking the alias address in the second database to the base address in the first database.

BACKGROUND

The present invention relates to the electrical, electronic, andcomputer arts, and more specifically, to address databases.

Electronic navigation systems specify streets and roads in terms ofgeographical coordinates of their endpoints and intersections with otherstreets and roads. The electronic navigation systems develop directionsbetween origin and destination street addresses based generally ontraversing a sequence of road-and-street geographical coordinates thatform a shortest route between the geographical coordinates of the inputorigin and destination street addresses. Thus, in order to obtain thegeographic coordinates of the origin and destination street addresses(“geocoding”), the electronic navigation systems rely on addressdatabases that correlate geographic coordinates to street addresses.These address databases also are useful for other purposes, e.g.,demographic data collection, marketing campaigns, epidemiology, etc.

SUMMARY

There may be multiple address databases a first of which has GPScoordinates correlated to addresses and a second of which has onlyaddresses and other data (e.g., demographic data or epidemiologic data).In such case it is helpful to correlate the addresses of the seconddatabase to those of the first database, thereby making the GPScoordinates accessible for use with the second database in order topermit mapping the data of the second database. However, in the firstand second databases there may be entries with different addresses(different place names) that nevertheless correspond to the samepremises and geographic coordinates. For example, this can be the casewhen premises could be located in either of two overlappingneighborhoods (e.g., “Edgecliff” and “Double Bay” are two neighborhoodsthat overlap each other within the city of Sydney Australia; “Astoria”is part of the borough of “Queens” in New York City), or when themunicipality itself is misspelt (e.g., “Sydney” spelt as “Sidney”).

Principles of the invention provide techniques for generating a rankedlist of best fitting place names. In one aspect, an exemplary methodincludes the use of clustering to generate place name clusters, ascoring function for choosing the best matching clusters, and avalidation step for verifying that two clusters are in fact aliases(cluster similarity measure). Thus, the method includes collecting froma first database a plurality of first geographic coordinatescorresponding to a plurality of first addresses that include a firstplace name; collecting from the first database a plurality of secondgeographic coordinates corresponding to a plurality of second addressesthat include a second place name; and collecting from the first databasea plurality of third geographic coordinates corresponding to a pluralityof third addresses that include a third place name. Additionally, theexemplary method includes geographically clustering the plurality offirst geographic coordinates in at least one first cluster;geographically clustering the plurality of second geographic coordinatesin at least one second cluster; and geographically clustering theplurality of third geographic coordinates in at least one third cluster.The exemplary method further includes obtaining from the first databasea base address including the first place name and having basecoordinates; assessing the best fit of the base coordinates to thefirst, second, and third clusters; and based on the two best fitclusters, identifying the second or third place name as an alias placename for the first place name. The exemplary method further includesobtaining from a second database, which does not include geographiccoordinates, a fourth plurality of addresses including the alias placename; fuzzy matching the base address to an alias address among thefourth plurality of addresses; and producing updated versions of thefirst and second databases by linking the alias address in the seconddatabase to the base address in the first database.

An exemplary embodiment of the invention is a non-transitory computerreadable medium including computer executable instructions which whenexecuted by a computer cause the computer to perform the exemplarymethod.

One or more embodiments of the invention can be implemented in the formof an apparatus that includes a memory and at least one processor thatis coupled to the memory and operative to implement the exemplarymethod.

As used herein, “facilitating” an action includes performing the action,making the action easier, helping to carry the action out, or causingthe action to be performed. Thus, by way of example and not limitation,instructions executing on one processor might facilitate an actioncarried out by instructions executing on a remote processor, by sendingappropriate data or commands to cause or aid the action to be performed.For the avoidance of doubt, where an actor facilitates an action byother than performing the action, the action is nevertheless performedby some entity or combination of entities.

One or more embodiments of the invention or elements thereof can beimplemented in the form of a computer program product including acomputer readable storage medium with computer usable program code forperforming the method steps indicated. Furthermore, one or moreembodiments of the invention or elements thereof can be implemented inthe form of a system (or apparatus) including a memory, and at least oneprocessor that is coupled to the memory and operative to performexemplary method steps. Yet further, in another aspect, one or moreembodiments of the invention or elements thereof can be implemented inthe form of means for carrying out one or more of the method stepsdescribed herein; the means can include (i) hardware module(s), (ii)software module(s) stored in a computer readable storage medium (ormultiple such media) and implemented on a hardware processor, or (iii) acombination of (i) and (ii); any of (i)-(iii) implement the specifictechniques set forth herein.

Techniques of the present invention can provide substantial beneficialtechnical effects. For example, one or more embodiments provide one ormore of:

Improved quality of address matching results.

Automated handling of moveable region borders.

These and other features and advantages of the present invention willbecome apparent from the following detailed description of illustrativeembodiments thereof, which is to be read in connection with theaccompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a cloud computing environment according to an embodimentof the present invention;

FIG. 2 depicts abstraction model layers according to an embodiment ofthe present invention;

FIG. 3 illustrates an address matching problem;

FIG. 4 illustrates addressed premises within overlapping neighborhoods;

FIG. 5 depicts in flowchart form a method for detecting aliasedaddresses according to the invention;

FIG. 6 depicts in flowchart form a method for using aliased addresses toestablish a best match between a first address and a plurality of secondaddresses; and

FIG. 7 depicts a computer system for implementing one or more aspectsand/or elements of the invention, also representative of a cloudcomputing node according to an embodiment of the present invention.

DETAILED DESCRIPTION

It is understood in advance that although this disclosure includes adetailed description on cloud computing, implementation of the teachingsrecited herein are not limited to a cloud computing environment. Rather,embodiments of the present invention are capable of being implemented inconjunction with any other type of computing environment now known orlater developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g. networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as Follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported providing transparency for both theprovider and consumer of the utilized service.

Service Models are as Follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based email). Theconsumer does not manage or control the underlying cloud infrastructureincluding network, servers, operating systems, storage, or evenindividual application capabilities, with the possible exception oflimited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as Follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting for loadbalancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure comprising anetwork of interconnected nodes.

Referring now to FIG. 1, illustrative cloud computing environment 50 isdepicted. As shown, cloud computing environment 50 includes one or morecloud computing nodes 10 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Nodes 10 maycommunicate with one another. They may be grouped (not shown) physicallyor virtually, in one or more networks, such as Private, Community,Public, or Hybrid clouds as described hereinabove, or a combinationthereof. This allows cloud computing environment 50 to offerinfrastructure, platforms and/or software as services for which a cloudconsumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 54A-N shownin FIG. 1 are intended to be illustrative only and that computing nodes10 and cloud computing environment 50 can communicate with any type ofcomputerized device over any type of network and/or network addressableconnection (e.g., using a web browser).

Referring now to FIG. 2, a set of functional abstraction layers providedby cloud computing environment 50 (FIG. 1) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 2 are intended to be illustrative only and embodiments of theinvention are not limited thereto. As depicted, the following layers andcorresponding functions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include: mainframes 61; RISC(Reduced Instruction Set Computer) architecture based servers 62;servers 63; blade servers 64; storage devices 65; and networks andnetworking components 66. In some embodiments, software componentsinclude network application server software 67 and database software 68.

Virtualization layer 70 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers71; virtual storage 72; virtual networks 73, including virtual privatenetworks; virtual applications and operating systems 74; and virtualclients 75.

In one example, management layer 80 may provide the functions describedbelow. Resource provisioning 81 provides dynamic procurement ofcomputing resources and other resources that are utilized to performtasks within the cloud computing environment. Metering and Pricing 82provide cost tracking as resources are utilized within the cloudcomputing environment, and billing or invoicing for consumption of theseresources. In one example, these resources may include applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal 83 provides access to the cloud computing environment forconsumers and system administrators. Service level management 84provides cloud computing resource allocation and management such thatrequired service levels are met. Service Level Agreement (SLA) planningand fulfillment 85 provide pre-arrangement for, and procurement of,cloud computing resources for which a future requirement is anticipatedin accordance with an SLA.

Workloads layer 90 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation 91; software development and lifecycle management 92; virtualclassroom education delivery 93; data analytics processing 94;transaction processing 95; and address matching 96.

Referring to FIG. 3, the invention is intended to resolve a problem inthe matching of street addresses among multiple databases. A firstdatabase 300 has a first street address (base address) 302 that isassociated with a first set of geographic coordinates (base coordinates)304. The base address 302 includes several place names at differentgeographic levels, i.e. a house number, a street name, a neighborhood,and a municipality. A second database 310 has second and third streetaddresses 312, 313 that are not associated with geographic coordinates.Either of the second or third street addresses 312, 313 might be analias address 314 of the base address 302, in other words, might referto the same premises. In case the alias address 314 existed, then itwould become possible to link all the data associated with the baseaddress 302, including the base coordinates 304, to the alias address314. Such a linkage of data would significantly enhance the usefulnessof the second database 310.

Each of the street addresses 302, 312, 313 includes several place namesat different geographic levels. At some geographic levels, the placenames of one or more of the other street addresses may match the placenames of the base address. For example, the base address 302 includes“House 12345” which is an exact match for the house numbers of thesecond and third street addresses 312, 313. However, the base address302 then includes “Burnleigh Court” which does not match either“Bernleigh Court” (in the second street address 312) or “Burnley Court”(in the third street address 313). Further, the base address 302includes “Edgecliff” which is an exact match for the neighborhood of thesecond street address 312 but not for the neighborhood of the thirdstreet address 313. Finally, the base address 302 includes “Sydney”which is an exact match for the municipality of the second streetaddress 312 but not for the municipality of the third street address313.

Referring now to FIG. 4, however, exact matches are not dispositive. Forexample, the “Edgecliff” and “Double Bay” neighborhoods 402, 404 ofSydney overlap so that a resident of one neighborhood might mistakenlyenter the other neighborhood on a form that is used to generate a streetaddress in the first or second database. Further, while entering theform data there might be an error either of typography or of opticalcharacter recognition, such that either “Bernleigh” or “Burnley” mightbe obtained for an actual place name of “Burnleigh”. Additionally,“Sidney” is a common misspelling of “Sydney”. Thus, it is not possibleto rule out or confirm by simple comparison of place names whethereither of the other street addresses 312, 313 is in fact the aliasaddress 314 of the base address 302.

When attempting to find a match for base address 302, the candidatematch of the second address 312 can be generated using fuzzy matchingtechniques. But in some cases, the correct match is Address B (the thirdaddress 313) and it can only be generated by substituting of aliasessuch as Edgecliff for Double Bay, prior to fuzzy matching.

Accordingly, the invention is intended to resolve the problem where astreet address might include either a first place name (e.g.,“Edgecliff”) or a second place name (e.g., “Double Bay”). This problemcan occur for a street address 302, 312, or 313 that is located withinan overlap of two neighborhoods 402 (“Edgecliff”), 404 (“Double Bay”),as shown by the map of addressed premises in FIG. 4.

The invention resolves the problem of multiple potential place namesusing a plurality of street addresses and corresponding geographiccoordinates that are collected from the first database 300. Given asufficiently large group of street addresses from the first database, itcan be assumed that the plurality of street addresses will contain allthe permutations of place names discussed above (i.e., “Burnleigh”,“Bernleigh”, “Burnley” as well as “Sydney” and “Sidney”). By theexpedient of clustering the different place names based on thecorresponding geographic coordinates of their respective streetaddresses, it becomes possible to determine whether certain place namesare indeed aliases for other place names.

In other words, we can understand that “Edgecliff” is an alias for“Double Bay” by taking the geographic coordinates of the base address302 and finding the best matching clusters. A ranked list will bereturned with “Edgecliff” and “Double Bay” at the top. The ranked listcan be generated from the base coordinates 304 by finding n nearestneighbors of the base coordinates 304 in each place name cluster, thencalculating an average distance p_score from the base coordinates 304 tothe nearest neighbors. The lower the value of p_score for a givencluster, the better the base coordinates 304 match that cluster.Accordingly, the place name clusters can be ranked based on theirp_score values.

The method of ranked lists can be validated to not indicate falsematches in case the p_score values of the two “best fit” clusters differby more than a pre-determined threshold (e.g., the p_score for the bestcluster is 60 meters whereas the p_score for the second best cluster is600 meters). Such a difference would rule out an alias relationshipbetween the place name of the best cluster and the place name of thesecond best cluster.

Another mode of validating the “best fit” clusters to be aliases is bycalculating the convex hulls CV1, CV2 of a pair of clusters CL1, CL2,then dividing the intersected area of the hulls, area (CV1 n CV2)̂2, bythe area product of the hulls, area (CV1)*area (CV2). A result closer to1 indicates a greater likelihood that the two “best fit” clusterscorrespond to alias place names. A result less than a certain threshold(e.g., less than 0.7) would indicate that the two “best fit” clustersare not likely to correspond to alias place names.

A similar process can be performed for “Sydney” and “Sidney”. Forexample, clustering all of the “Sydney” street addresses and all of the“Sidney” street addresses from the first database, and then validatingthe clusters as discussed above, may reveal that the geographiccoordinates corresponding to these different place names do in factoverlap and interleave so that the place names may be consideredinterchangeable (aliases to each other). On the other hand, clusteringthe street addresses of these different place names may reveal thatresidents of some streets or neighborhoods refer to their municipalityas “Sydney” while residents of other streets or neighborhoods prefer“Sidney”, so that the two place names are not interchangeable(distinguishing otherwise similar addresses). In either case, dataobtained from geographic clustering on the first database 300 enablesresolution of potential alias addresses. Then, by substituting aliases,fuzzy matching techniques can now be used to correctly match the baseaddress 302 to the third address 313 from the second database 310.

Given the discussion thus far, and referring specifically to FIG. 5 inthe drawings, it will be appreciated that, in general terms, anexemplary method 500, according to an aspect of the invention, includesthe use of clustering to generate place name clusters, a scoringfunction for choosing the best matching clusters, and a validation stepfor verifying that two clusters are in fact aliases (cluster similaritymeasure). Thus, the method 500 includes collecting 502 from a firstdatabase 300 a plurality of first geographic coordinates 506corresponding to a plurality of first addresses 508 that include a firstplace name 510; collecting 502 from the first database 300 a pluralityof second geographic coordinates 514 corresponding to a plurality ofsecond addresses 516 that include a second place name 518; andcollecting 502 from the first database 300 a plurality of thirdgeographic coordinates 522 corresponding to a plurality of thirdaddresses 524 that include a third place name 526. Additionally, theexemplary method includes geographically clustering 528 the plurality offirst geographic coordinates 506 in at least one first cluster 530;geographically clustering 528 the plurality of second geographiccoordinates 514 in at least one second cluster 532; and geographicallyclustering 528 the plurality of third geographic coordinates 522 in atleast one third cluster 534. The exemplary method further includesobtaining 536 from the first database 300 a base address 302 includingthe first place name 510 and having base coordinates 304; assessing 538the best fit of the base coordinates 304 to the first, second, and thirdclusters 530, 532, 534; and based on the two best fit clusters,identifying 542 the second or third place name 518, 526 as an aliasplace name 544 for the first place name 510.

According to certain implementations of the exemplary method, theclustering 528 makes use of density based clustering algorithms, such asDBScan, that are based on connecting points within defined distancethresholds corresponding to a place name level (e.g., the clusters for astreet name such as “Burnleigh” or “Burnley” could be obtained using adistance threshold of 500 meters whereas the clusters for a neighborhoodname such as “Edgecliff” or “Double Bay” could be obtained using adistance threshold of 1.5 kilometers). According to particularimplementations of the exemplary method, assessing the best fit 538includes finding n nearest neighbors of the base coordinates within eachof the clusters, calculating an average distance from the basecoordinates to the n nearest neighbors, and ranking the clusters so thatthe cluster with the smallest average distance is the best fitting.According to certain embodiments of the invention, identifying 542 analias place name includes validating 540 that the two best fit clustersare alias clusters by deriving a convex hull of each of the two best fitclusters, calculating an area of each convex hull, calculating anintersected area of the two convex hulls, and calculating the square ofthe intersected area divided by the product of the convex hull areas,wherein a result closer to 1.0 indicates a greater likelihood that thetwo best fit clusters are alias clusters. For example, a result greaterthan 0.7 indicates the two best fit clusters are alias clusters.

Referring now to FIG. 6, it is apparent that the exemplary methodfurther includes obtaining 601 from a second database 310, which doesnot include geographic coordinates, a fourth plurality of addresses 602including the alias place name 544; fuzzy matching 604 the base address302 to an alias address 314 among the fourth plurality of addresses; andlinking 606 the alias address 314 in the second database 310 to the baseaddress 302 in the first database 300, to produce updated versions ofthe first and second databases. According to certain implementations ofthe exemplary method, linking the base address to the alias addressincludes linking the base coordinates to the alias address.

Another implementation of the exemplary method of updating a pluralityof databases storing place names includes collecting from a firstdatabase a plurality of first geographic coordinates corresponding to aplurality of first addresses including a first place name; collectingfrom the first database a plurality of second geographic coordinatescorresponding to a plurality of second addresses including a secondplace name; geographically clustering the plurality of first geographiccoordinates in at least one first cluster; geographically clustering theplurality of second geographic coordinates in at least one secondcluster; calculating convex hulls of the first and second clusters;dividing the square of the intersected area of the convex hulls by thearea product of the hulls, and comparing the result to a threshold; inresponse to the result exceeding the threshold, identifying the secondplace name as an alias place name for the first place name; obtainingfrom the first database base geographic coordinates corresponding to abase address including the first place name; obtaining from a seconddatabase, which does not include geographic coordinates, a plurality ofaddresses including the alias place name; fuzzy matching the baseaddress to an alias address among the plurality of addresses includingthe alias place name; and linking the alias address in the seconddatabase to the base address in the first database, to produce updatedversions of the first and second databases.

An exemplary embodiment of the invention is a non-transitory computerreadable medium including computer executable instructions which whenexecuted by a computer cause the computer to perform any of theexemplary methods above discussed.

One or more embodiments of the invention, or elements thereof, can beimplemented in the form of an apparatus including a memory and at leastone processor that is coupled to the memory and operative to performexemplary method steps. FIG. 7 depicts a computer system forimplementing one or more aspects and/or elements of the invention, alsorepresentative of a cloud computing node according to an embodiment ofthe present invention. Referring now to FIG. 7, cloud computing node 10is only one example of a suitable cloud computing node and is notintended to suggest any limitation as to the scope of use orfunctionality of embodiments of the invention described herein.Regardless, cloud computing node 10 is capable of being implementedand/or performing any of the functionality set forth hereinabove.

In cloud computing node 10 there is a computer system/server 12, whichis operational with numerous other general purpose or special purposecomputing system environments or configurations. Examples of well-knowncomputing systems, environments, and/or configurations that may besuitable for use with computer system/server 12 include, but are notlimited to, personal computer systems, server computer systems, thinclients, thick clients, handheld or laptop devices, multiprocessorsystems, microprocessor-based systems, set top boxes, programmableconsumer electronics, network PCs, minicomputer systems, mainframecomputer systems, and distributed cloud computing environments thatinclude any of the above systems or devices, and the like.

Computer system/server 12 may be described in the general context ofcomputer system executable instructions, such as program modules, beingexecuted by a computer system. Generally, program modules may includeroutines, programs, objects, components, logic, data structures, and soon that perform particular tasks or implement particular abstract datatypes. Computer system/server 12 may be practiced in distributed cloudcomputing environments where tasks are performed by remote processingdevices that are linked through a communications network. In adistributed cloud computing environment, program modules may be locatedin both local and remote computer system storage media including memorystorage devices.

As shown in FIG. 7, computer system/server 12 in cloud computing node 10is shown in the form of a general-purpose computing device. Thecomponents of computer system/server 12 may include, but are not limitedto, one or more processors or processing units 16, a system memory 28,and a bus 18 that couples various system components including systemmemory 28 to processor 16.

Bus 18 represents one or more of any of several types of bus structures,including a memory bus or memory controller, a peripheral bus, anaccelerated graphics port, and a processor or local bus using any of avariety of bus architectures. By way of example, and not limitation,such architectures include Industry Standard Architecture (ISA) bus,Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, VideoElectronics Standards Association (VESA) local bus, and PeripheralComponent Interconnect (PCI) bus.

Computer system/server 12 typically includes a variety of computersystem readable media. Such media may be any available media that isaccessible by computer system/server 12, and it includes both volatileand non-volatile media, removable and non-removable media.

System memory 28 can include computer system readable media in the formof volatile memory, such as random access memory (RAM) 30 and/or cachememory 32. Computer system/server 12 may further include otherremovable/non-removable, volatile/non-volatile computer system storagemedia. By way of example only, storage system 34 can be provided forreading from and writing to a non-removable, non-volatile magnetic media(not shown and typically called a “hard drive”). Although not shown, amagnetic disk drive for reading from and writing to a removable,non-volatile magnetic disk (e.g., a “floppy disk”), and an optical diskdrive for reading from or writing to a removable, non-volatile opticaldisk such as a CD-ROM, DVD-ROM or other optical media can be provided.In such instances, each can be connected to bus 18 by one or more datamedia interfaces. As will be further depicted and described below,memory 28 may include at least one program product having a set (e.g.,at least one) of program modules that are configured to carry out thefunctions of embodiments of the invention.

Program/utility 40, having a set (at least one) of program modules 42,may be stored in memory 28 by way of example, and not limitation, aswell as an operating system, one or more application programs, otherprogram modules, and program data. Each of the operating system, one ormore application programs, other program modules, and program data orsome combination thereof, may include an implementation of a networkingenvironment. Program modules 42 generally carry out the functions and/ormethodologies of embodiments of the invention as described herein.

Computer system/server 12 may also communicate with one or more externaldevices 14 such as a keyboard, a pointing device, a display 24, etc.;one or more devices that enable a user to interact with computersystem/server 12; and/or any devices (e.g., network card, modem, etc.)that enable computer system/server 12 to communicate with one or moreother computing devices. Such communication can occur via Input/Output(I/O) interfaces 22. Still yet, computer system/server 12 cancommunicate with one or more networks such as a local area network(LAN), a general wide area network (WAN), and/or a public network (e.g.,the Internet) via network adapter 20. As depicted, network adapter 20communicates with the other components of computer system/server 12 viabus 18. It should be understood that although not shown, other hardwareand/or software components could be used in conjunction with computersystem/server 12. Examples, include, but are not limited to: microcode,device drivers, redundant processing units, and external disk drivearrays, RAID systems, tape drives, and data archival storage systems,etc.

Thus, one or more embodiments can make use of software running on ageneral purpose computer or workstation. With reference to FIG. 7, suchan implementation might employ, for example, a processor 16, a memory28, and an input/output interface 22 to a display 24 and externaldevice(s) 14 such as a keyboard, a pointing device, or the like. Theterm “processor” as used herein is intended to include any processingdevice, such as, for example, one that includes a CPU (centralprocessing unit) and/or other forms of processing circuitry. Further,the term “processor” may refer to more than one individual processor.The term “memory” is intended to include memory associated with aprocessor or CPU, such as, for example, RAM (random access memory) 30,ROM (read only memory), a fixed memory device (for example, hard drive34), a removable memory device (for example, diskette), a flash memoryand the like. In addition, the phrase “input/output interface” as usedherein, is intended to contemplate an interface to, for example, one ormore mechanisms for inputting data to the processing unit (for example,mouse), and one or more mechanisms for providing results associated withthe processing unit (for example, printer). The processor 16, memory 28,and input/output interface 22 can be interconnected, for example, viabus 18 as part of a data processing unit 12. Suitable interconnections,for example via bus 18, can also be provided to a network interface 20,such as a network card, which can be provided to interface with acomputer network, and to a media interface, such as a diskette or CD-ROMdrive, which can be provided to interface with suitable media.

Accordingly, computer software including instructions or code forperforming the methodologies of the invention, as described herein, maybe stored in one or more of the associated memory devices (for example,ROM, fixed or removable memory) and, when ready to be utilized, loadedin part or in whole (for example, into RAM) and implemented by a CPU.Such software could include, but is not limited to, firmware, residentsoftware, microcode, and the like.

A data processing system suitable for storing and/or executing programcode will include at least one processor 16 coupled directly orindirectly to memory elements 28 through a system bus 18. The memoryelements can include local memory employed during actual implementationof the program code, bulk storage, and cache memories 32 which providetemporary storage of at least some program code in order to reduce thenumber of times code must be retrieved from bulk storage duringimplementation.

Input/output or I/O devices (including but not limited to keyboards,displays, pointing devices, and the like) can be coupled to the systemeither directly or through intervening I/O controllers.

Network adapters 20 may also be coupled to the system to enable the dataprocessing system to become coupled to other data processing systems orremote printers or storage devices through intervening private or publicnetworks. Modems, cable modem and Ethernet cards are just a few of thecurrently available types of network adapters.

As used herein, including the claims, a “server” includes a physicaldata processing system (for example, system 12 as shown in FIG. 7)running a server program. It will be understood that such a physicalserver may or may not include a display and keyboard.

One or more embodiments can be at least partially implemented in thecontext of a cloud or virtual machine environment, although this isexemplary and non-limiting. Reference is made back to FIGS. 1-2 andaccompanying text.

It should be noted that any of the methods described herein can includean additional step of providing a system comprising distinct softwaremodules embodied on a computer readable storage medium; the modules caninclude, for example, any or all of the appropriate elements depicted inthe block diagrams and/or described herein; by way of example and notlimitation, any one, some or all of the modules/blocks and orsub-modules/sub-blocks described. The method steps can then be carriedout using the distinct software modules and/or sub-modules of thesystem, as described above, executing on one or more hardware processorssuch as 16. Further, a computer program product can include acomputer-readable storage medium with code adapted to be implemented tocarry out one or more method steps described herein, including theprovision of the system with the distinct software modules.

One example of user interface that could be employed in some cases ishypertext markup language (HTML) code served out by a server or thelike, to a browser of a computing device of a user. The HTML is parsedby the browser on the user's computing device to create a graphical userinterface (GUI).

Exemplary System and Article of Manufacture Details

The present invention may be a system, a method, and/or a computerprogram product. The computer program product may include a computerreadable storage medium (or media) having computer readable programinstructions thereon for causing a processor to carry out aspects of thepresent invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, configuration data for integrated circuitry, oreither source code or object code written in any combination of one ormore programming languages, including an object oriented programminglanguage such as Smalltalk, C++, or the like, and procedural programminglanguages, such as the “C” programming language or similar programminglanguages. The computer readable program instructions may executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer or entirely on the remote computer or server. Inthe latter scenario, the remote computer may be connected to the user'scomputer through any type of network, including a local area network(LAN) or a wide area network (WAN), or the connection may be made to anexternal computer (for example, through the Internet using an InternetService Provider). In some embodiments, electronic circuitry including,for example, programmable logic circuitry, field-programmable gatearrays (FPGA), or programmable logic arrays (PLA) may execute thecomputer readable program instructions by utilizing state information ofthe computer readable program instructions to personalize the electroniccircuitry, in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the blocks may occur out of theorder noted in the Figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the describedembodiments. The terminology used herein was chosen to best explain theprinciples of the embodiments, the practical application or technicalimprovement over technologies found in the marketplace, or to enableothers of ordinary skill in the art to understand the embodimentsdisclosed herein.

1.-7. (canceled)
 8. A non-transitory computer readable medium comprisingcomputer executable instructions which when executed by a computer causethe computer to perform a method of updating a plurality of databasesstoring place names, the method comprising: collecting from a firstdatabase a plurality of first geographic coordinates corresponding to aplurality of first addresses including a first place name; collectingfrom the first database a plurality of second geographic coordinatescorresponding to a plurality of second addresses including a secondplace name; collecting from the first database a plurality of thirdgeographic coordinates corresponding to a plurality of third addressesincluding a third place name; geographically clustering the plurality offirst geographic coordinates in at least one first cluster;geographically clustering the plurality of second geographic coordinatesin at least one second cluster; geographically clustering the pluralityof third geographic coordinates in at least one third cluster; obtainingfrom the first database a base address including the first place nameand having base coordinates; assessing the best fit of the basecoordinates to the first, second, and third clusters; based on the twobest fit clusters, identifying the second or third place name as analias place name for the first place name; obtaining from a seconddatabase, which does not include geographic coordinates, a fourthplurality of addresses including the alias place name; fuzzy matchingthe base address to an alias address among the fourth plurality ofaddresses; and producing updated versions of the first and seconddatabases by linking the alias address in the second database to thebase address in the first database.
 9. The medium of claim 8 whereineach step of clustering uses density based clustering based onconnecting points within defined distance thresholds corresponding to aplace name level.
 10. The medium of claim 8 wherein each step ofclustering uses an algorithm that does not require the number ofclusters to be passed in as a parameter of the algorithm.
 11. The mediumof claim 8 wherein assessing the best fit includes finding n nearestneighbors of the base coordinates within each of the clusters,calculating an average distance from the base coordinates to the nnearest neighbors, and ranking the clusters so that the cluster with thesmallest average distance is the best fitting.
 12. The medium of claim 8wherein identifying an alias place name includes validating that the twobest fit clusters are alias clusters by deriving a convex hull of eachof the two best fit clusters, calculating an area of each convex hull,calculating an intersected area of the two convex hulls, and calculatingthe square of the intersected area divided by the product of the convexhull areas, wherein a result closer to 1.0 indicates a greaterlikelihood that the two best fit clusters are alias clusters.
 13. Themedium of claim 12 wherein a result greater than 0.7 indicates the twobest fit clusters are alias clusters.
 14. The medium of claim 8 whereinlinking the base address to the alias address includes linking the basecoordinates to the alias address.
 15. An apparatus comprising: a memory;and at least one processor, coupled to said memory, and operative toimplement a method of updating a plurality of databases storing placenames, the method comprising: collecting from a first database stored inthe memory a plurality of first geographic coordinates corresponding toa plurality of first addresses including a first place name; collectingfrom the first database a plurality of second geographic coordinatescorresponding to a plurality of second addresses including a secondplace name; collecting from the first database a plurality of thirdgeographic coordinates corresponding to a plurality of third addressesincluding a third place name; geographically clustering the plurality offirst geographic coordinates in at least one first cluster;geographically clustering the plurality of second geographic coordinatesin at least one second cluster; geographically clustering the pluralityof third geographic coordinates in at least one third cluster; obtainingfrom the first database a base address including the first place nameand having base coordinates; assessing the best fit of the basecoordinates to the first, second, and third clusters; based on the twobest fit clusters, identifying the second or third place name as analias place name for the first place name; obtaining from a seconddatabase stored in the memory, which does not include geographiccoordinates, a fourth plurality of addresses including the alias placename; fuzzy matching the base address to an alias address among thefourth plurality of addresses; and producing updated versions of thefirst and second databases by linking the alias address in the seconddatabase to the base address in the first database.
 16. The apparatus ofclaim 15 wherein each step of clustering uses density based clusteringbased on connecting points within defined distance thresholdscorresponding to a place name level.
 17. The apparatus of claim 15wherein each step of clustering uses an algorithm that does not requirethe number of clusters to be passed in as a parameter of the algorithm.18. The apparatus of claim 15 wherein assessing the best fit includesfinding n nearest neighbors of the base coordinates within each of theclusters, calculating an average distance from the base coordinates tothe n nearest neighbors, and ranking the clusters so that the clusterwith the smallest average distance is the best fitting.
 19. Theapparatus of claim 15 wherein identifying an alias place name includesvalidating that the two best fit clusters are alias clusters by derivinga convex hull of each of the two best fit clusters, calculating an areaof each convex hull, calculating an intersected area of the two convexhulls, and calculating the square of the intersected area divided by theproduct of the convex hull areas, wherein a result closer to 1.0indicates a greater likelihood that the two best fit clusters are aliasclusters.
 20. The apparatus of claim 15 wherein linking the base addressto the alias address includes linking the base coordinates to the aliasaddress.